Pavement roughness index estimation and anomaly detection using smartphones

被引:28
|
作者
Yu, Qiqin [1 ]
Fang, Yihai [1 ]
Wix, Richard [2 ]
机构
[1] Monash Univ, Dept Civil Engn, Melbourne, Australia
[2] Australian Rd Res Board, Melbourne, Australia
基金
澳大利亚研究理事会;
关键词
Pavement roughness; Roughness index; Surface distress; Smartphone; Algorithm; VEHICLE RESPONSES; FREQUENCY-DOMAIN; SYSTEM; RECONSTRUCTION; ACCELEROMETER; QUALITY; ROADS;
D O I
10.1016/j.autcon.2022.104409
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The prevalence of smartphones among vehicle drivers presents exciting opportunities in assessing pavement roughness in a more efficient and cost-effective manner, compared with using conventional instruments. This paper describes the body of knowledge in smartphone-based roughness assessment, reports knowledge gaps and casts light on future research directions. First, a systematic literature search found 192 academic publications in relevant fields. These works were critically reviewed with regard to sensor selection, pre-processing methods, and assessment algorithms. Special attention was given to practical factors that are expected to affect the accuracy and robustness of smartphone-based methods, including data collection speed, vehicle type, smartphone specifications and mounting configuration. Findings from this research are expected to provide a thorough understanding of the potentials and limitations of smartphone-based roughness assessment methods and inform future research and practices in this domain.
引用
收藏
页数:20
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